Heart rate sensors are commonly used for monitoring and characterizing sports performances. Most commonly, they are based on electric measurement of heart activity using electrodes placed on the skin of a person, i.e. using an electrocardiographic (ECG) measurement. Heart rate can be determined by detecting individual heartbeats from the ECG signal and counting their frequency. Heart rate as such is an important characteristic parameter of the performance but it can also be used to estimate for example energy consumption of the person. This is also very common in existing sports monitoring equipment.
It has been found that in certain situations heart rate is not a good indicator of energy consumption and its use results in erroneous energy consumption values. Correction of energy consumption can be carried out to some extent using other data available, see for example FI Application No 20115150 or FI Application No 20105310, but even that does not result in satisfactory results in all cases. EP 1862117, on the other hand, discloses a method for calibrating calculation of energy consumption using activity data, in particular by taking into account the delay at which the heart rate follows the changes in activity level.
Determining energy consumption from heart rate is particularly challenging in low-intensity performances, i.e. when heart activity due to the physical performance is only slightly or moderately above the resting heart activity. The heart rate is influenced not only by the physical effort, but also by psychological factors and other factors stimulating the neural network, such as excitement, and error from such contributions is relatively high in low-intensity performances. There are no reliable methods available for taking such errors into account.
Energy consumption can also be determined by measuring or estimating ventilation during the performance, but that approach demands instrumentation which is impractical in training sessions. Alternatively, energy ventilation can be estimated based on inter-beat intervals of the ECG signal, see for example FI Application No 20086146, has a considerable source of error due to physiological constraints and measurement constraints.
Thus, there is a need for improved method for determining energy consumption in versatile training situations.